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Zalo Traffic Sign Dataset

50867446
Tagself-driving
Taskobject detection
Release YearMade in 2020
Licenseunknown

Introduction #

The Zalo Traffic Sign Detection 2020 Dataset presents a significant challenge yet is highly suitable for traffic sign detection applications in the diverse traffic conditions of Vietnam. Comprising 4,500 images sized at 1622x626 pixels, the dataset was curated by crawling Google Street View Map across various locations in Vietnam. The task entails detecting seven prevalent types of traffic signs: no entry, no parking/waiting, no turning, max speed, other prohibition signs, warning, and mandatory. Notably, the dataset poses considerable challenges due to the majority of objects of interest being extremely small, often less than 10x10 pixels in size. Additionally, it encompasses a wide array of scenes, ranging from urban areas to rural landscapes and from bustling city streets to secluded highways. The dataset is partitioned into two subsets: the train set, comprising 4,000 images, and the test set, comprising 500 images. Although the size of images of the Zalo dataset is large, traffic signs are very small in comparison to the whole image because the signs are very far from the camera.

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Dataset LinkHomepageDataset LinkResearch Paper

Summary #

Zalo Traffic Sign Detection 2020 Dataset is a dataset for an object detection task. It is used in the automotive industry.

The dataset consists of 5086 images with 10892 labeled objects belonging to 7 different classes including warning, no parking/waiting, other prohibition signs, and other: no entry, mandatory, max speed, and no turning.

Images in the Zalo Traffic Sign dataset have bounding box annotations. There are 586 (12% of the total) unlabeled images (i.e. without annotations). There are 2 splits in the dataset: train (4500 images) and test (586 images). Additionally, every image marked with street id tag. The dataset was released in 2020 by the Zalo AI, Vietnam.

Dataset Poster

Explore #

Zalo Traffic Sign dataset has 5086 images. Click on one of the examples below or open "Explore" tool anytime you need to view dataset images with annotations. This tool has extended visualization capabilities like zoom, translation, objects table, custom filters and more. Hover the mouse over the images to hide or show annotations.

OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
OpenSample annotation mask from Zalo Traffic SignSample image from Zalo Traffic Sign
πŸ‘€
Have a look at 5086 images
Because of dataset's license preview is limited to 12 images
View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 7 annotation classes in the dataset. Find the general statistics and balances for every class in the table below. Click any row to preview images that have labels of the selected class. Sort by column to find the most rare or prevalent classes.

Search
Rows 1-7 of 7
Class
γ…€
Images
γ…€
Objects
γ…€
Count on image
average
Area on image
average
warningβž”
rectangle
1853
3049
1.65
0.16%
no parking/waitingβž”
rectangle
1578
2220
1.41
0.18%
other prohibition signsβž”
rectangle
1115
1784
1.6
0.16%
no entryβž”
rectangle
1040
1415
1.36
0.06%
mandatoryβž”
rectangle
789
1021
1.29
0.08%
max speedβž”
rectangle
441
847
1.92
0.16%
no turningβž”
rectangle
438
556
1.27
0.2%

Co-occurrence matrix #

Co-occurrence matrix is an extremely valuable tool that shows you the images for every pair of classes: how many images have objects of both classes at the same time. If you click any cell, you will see those images. We added the tooltip with an explanation for every cell for your convenience, just hover the mouse over a cell to preview the description.

Images #

Explore every single image in the dataset with respect to the number of annotations of each class it has. Click a row to preview selected image. Sort by any column to find anomalies and edge cases. Use horizontal scroll if the table has many columns for a large number of classes in the dataset.

Object distribution #

Interactive heatmap chart for every class with object distribution shows how many images are in the dataset with a certain number of objects of a specific class. Users can click cell and see the list of all corresponding images.

Class sizes #

The table below gives various size properties of objects for every class. Click a row to see the image with annotations of the selected class. Sort columns to find classes with the smallest or largest objects or understand the size differences between classes.

Search
Rows 1-7 of 7
Class
Object count
Avg area
Max area
Min area
Min height
Min height
Max height
Max height
Avg height
Avg height
Min width
Min width
Max width
Max width
warning
rectangle
3049
0.12%
4.74%
0%
4px
0.64%
245px
39.14%
24px
3.88%
4px
0.25%
211px
13.01%
no parking/waiting
rectangle
2220
0.14%
5.42%
0%
4px
0.64%
200px
31.95%
29px
4.58%
4px
0.25%
275px
16.95%
other prohibition signs
rectangle
1784
0.11%
4.48%
0%
4px
0.64%
202px
32.27%
25px
4.06%
4px
0.25%
253px
15.6%
no entry
rectangle
1415
0.06%
1.5%
0%
3px
0.48%
124px
19.81%
18px
2.84%
3px
0.18%
123px
7.58%
mandatory
rectangle
1021
0.07%
2.73%
0%
3px
0.48%
176px
28.12%
19px
3.1%
4px
0.25%
274px
16.89%
max speed
rectangle
847
0.09%
2.23%
0%
4px
0.64%
120px
19.17%
24px
3.85%
4px
0.25%
210px
12.95%
no turning
rectangle
556
0.17%
2.43%
0%
5px
0.8%
155px
24.76%
31px
5.02%
6px
0.37%
190px
11.71%

Spatial Heatmap #

The heatmaps below give the spatial distributions of all objects for every class. These visualizations provide insights into the most probable and rare object locations on the image. It helps analyze objects' placements in a dataset.

Spatial Heatmap

Objects #

Table contains all 10892 objects. Click a row to preview an image with annotations, and use search or pagination to navigate. Sort columns to find outliers in the dataset.

Search
Rows 1-10 of 10892
Object ID
γ…€
Class
γ…€
Image name
click row to open
Image size
height x width
Height
γ…€
Height
γ…€
Width
γ…€
Width
γ…€
Area
γ…€
1βž”
warning
rectangle
7828.png
626 x 1622
18px
2.88%
19px
1.17%
0.03%
2βž”
max speed
rectangle
12474.png
626 x 1622
53px
8.47%
50px
3.08%
0.26%
3βž”
max speed
rectangle
12474.png
626 x 1622
57px
9.11%
54px
3.33%
0.3%
4βž”
other prohibition signs
rectangle
12474.png
626 x 1622
59px
9.42%
52px
3.21%
0.3%
5βž”
max speed
rectangle
12474.png
626 x 1622
35px
5.59%
37px
2.28%
0.13%
6βž”
no entry
rectangle
11046.png
626 x 1622
11px
1.76%
12px
0.74%
0.01%
7βž”
mandatory
rectangle
11046.png
626 x 1622
12px
1.92%
12px
0.74%
0.01%
8βž”
no entry
rectangle
11046.png
626 x 1622
12px
1.92%
12px
0.74%
0.01%
9βž”
mandatory
rectangle
11046.png
626 x 1622
12px
1.92%
12px
0.74%
0.01%
10βž”
no entry
rectangle
11046.png
626 x 1622
13px
2.08%
12px
0.74%
0.02%

License #

License is unknown for the Zalo Traffic Sign Detection 2020 Dataset dataset.

Source

Citation #

If you make use of the Zalo Traffic Sign data, please cite the following reference:

PASTE HERE CUSTOM CITATION FROM THE SOURCE URL

[Source](Thanh-Tung Ngo)

If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:

@misc{ visualization-tools-for-zalo-traffic-sign-dataset,
  title = { Visualization Tools for Zalo Traffic Sign Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/zalo-traffic-sign } },
  url = { https://datasetninja.com/zalo-traffic-sign },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jul },
  note = { visited on 2024-07-25 },
}

Download #

Please visit dataset homepage to download the data.

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